I am working with the leaflet R package. I have a zoning system made of polygons and I'd like to lay their IDs on top of them. Below is an illustration (with another software) of my objective.
Thanks for your suggestions!
Since there is no reproducible data, I decided to use one of my previous posts related to leaflet. There are two things you want to take away from this post: 1) you need to create a data frame containing center points of target regions, 2) you need to use addLabelOnlyMarkers(). You can achieve the first thing using gCentroid(). I added row names of the polygon data set (UK) as character to centers. This is used for labeling. You need to think what labels you use in your own case. Once this data set is ready, you want to use it in addLabelOnlyMarkers().
library(raster)
library(rgeos)
library(leaflet)
# Get UK polygon data
UK <- getData("GADM", country = "GB", level = 2)
# Find a center point for each region
centers <- data.frame(gCentroid(UK, byid = TRUE))
centers$region <- row.names(UK)
### Create dummy data
set.seed(111)
mydf <- data.frame(place = unique(UK$NAME_2),
value = sample.int(n = 1000, size = n_distinct(UK$NAME_2), replace = TRUE))
### Create five colors for fill
mypal <- colorQuantile(palette = "RdYlBu", domain = mydf$value, n = 5, reverse = TRUE)
leaflet() %>%
addProviderTiles("OpenStreetMap.Mapnik") %>%
setView(lat = 55, lng = -3, zoom = 6) %>%
addPolygons(data = UK,
stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.3,
fillColor = ~mypal(mydf$value),
popup = paste("Region: ", UK$NAME_2, "<br>",
"Value: ", mydf$value, "<br>")) %>%
addLabelOnlyMarkers(data = centers,
lng = ~x, lat = ~y, label = ~region,
labelOptions = labelOptions(noHide = TRUE, direction = 'top', textOnly = TRUE)) %>%
addLegend(position = "bottomright", pal = mypal, values = mydf$value,
title = "UK value",
opacity = 0.3)
Related
In the tiny example shown below, I have two features associated with each country (polygons) in the map, namely: randomA, randomB. Each feature has its own legend, so I armed a group named "randomA" containing the polygons coloured with feature randomA and its corresponding legend. I did the same for group "randomB". When the map is depicted, leaflet correctly shows or hides polygons for features "randomA" and "randomB". However legends are always shown stacked on the bottom right corner.
This is the code:
library(rgdal)
library(leaflet)
# From http://data.okfn.org/data/datasets/geo-boundaries-world-110m
countries <- readOGR("json/countries.geojson")
n <- nrow(countries)
# Add two random fields
set.seed(15)
countries#data$randomA <- rnorm(n, 1000, 250)
countries#data$randomB <- rnorm(n, 10000, 3000)
map <- leaflet(countries) %>% addTiles()
pal <- colorNumeric(
palette = "YlGnBu",
domain = countries$randomA
)
map <- map %>%
addPolygons(stroke = FALSE, smoothFactor = 0.2, fillOpacity = 1,
color = ~pal(randomA), group = "randomA"
) %>%
addLegend("bottomright", pal = pal, values = ~randomA,
title = "random A",
labFormat = labelFormat(prefix = "$"),
opacity = 1, group = "randomA"
)
qpal <- colorQuantile("RdYlBu", countries$gdp_md_est, n = 5)
map <- map %>%
addPolygons(stroke = FALSE, smoothFactor = 0.2, fillOpacity = 1,
color = ~qpal(randomB), group = "randomB"
) %>%
addLegend(
"bottomright",
pal = qpal,
values = ~randomB,
opacity = 1, group = "randomB"
)
# Finally control layers:
map <- map %>%
addLayersControl(
baseGroups = c("randomA", "randomB"),
position = "bottomleft",
options = layersControlOptions(collapsed = F)
)
map
A snapshot of the result is shown in the image below:
Also, in the actual problem I have to represent nine of these groups, so I wish I had all the legends in the same place.
Do you have any suggestion?
Try using overlay groups instead of base groups:
addLayersControl(
overlayGroups = c("randomA", "randomB"),
position = "bottomleft",
options = layersControlOptions(collapsed = F)
)
I'm trying to create a choropleth map in county level using leaflet R package and I actually do it. But when I check my data file and the hover text of any county I find that the values are not correct. For example check the Conejos county. Any explanation? Or a better way to process tha data and create this map without the mismatches?
Code:
library(raster)
library(leaflet)
library(tidyverse)
# Get USA polygon data
USA <- getData("GADM", country = "usa", level = 2)
### Get data
mydata <- read.csv("https://www.betydb.org/miscanthus_county_avg_yield.csv",
stringsAsFactors = FALSE) %>%
dplyr::select(COUNTY_NAME, Avg_yield)
### Check counties that exist in USA, but not in mydata
### Create a dummy data frame and bind it with mydata
mydata <- data.frame(COUNTY_NAME = setdiff(USA$NAME_2, mydata$COUNTY_NAME),
Avg_yield = NA,
stringsAsFactors = FALSE) %>%
bind_rows(mydata)
### Create a color palette
mypal <- colorNumeric(palette = "viridis", domain = mydata$Avg_yield)
leaflet() %>%
addProviderTiles("OpenStreetMap.Mapnik") %>%
setView(lat = 39.8283, lng = -98.5795, zoom = 4) %>%
addPolygons(data = USA, stroke = FALSE, smoothFactor = 0.2, fillOpacity = 0.3,
fillColor = ~mypal(mydata$Avg_yield),
popup = paste("Region: ", USA$NAME_2, "<br>",
"Avg_yield: ", mydata$Avg_yield, "<br>")) %>%
addLegend(position = "bottomleft", pal = mypal, values = mydata$Avg_yield,
title = "Avg_yield",
opacity = 1)
I am trying to create a high-quality map of a small part of the UK, without any distortions caused by the use of projections, and with the addition of markers consisting of text and symbols. Ultimately the goal is to write out a png or pdf file. An earlier, related question can be found here.
Having not used R in anger for several years, I have been wading through a morass of packages trying to find something suitable. Leaflet for R is promising, but although I can create a decent-looking map, add markers, and vary the colour of markers and so on using columns from a data frame, I have not been able to vary the size, colour, and text offsets used in the labelOptions argument.
The following reproducible example shows what I can achieve, and also where I am not succeeding. I would like the size of text label to vary according to the df.data$textsizes column. Given that the style argument takes a list of value pairs, that would seem difficult, and nothing has worked so far.
If am hoping that somebody can either suggest either a way to bend the wily labelOptions to my will, or a completely different approach to try.
require(leaflet)
require(magrittr)
df.entrynames <- c("Entry 1: Some text","Entry 2: More text")
df.lat <- c(51.509898,51.510736)
df.lon <- c(-0.1345093,-0.135190)
df.colors <-c("Blue","Red")
df.sizes <-c(36,12)
df.data <- data.frame(entrynames=df.entrynames,lat=df.lat,lon=df.lon,colors=df.colors,textsizes=df.sizes)
df.data$entrynames <- as.character(df.data$entrynames)
df.data$colors <- as.character(df.data$colors)
df.data$textsizes <- paste(df.data$textsizes,"px",sep="")
leaflet() %>% setView(lng = -0.134509, lat = 51.509898, zoom = 17) %>% addTiles() %>%
addCircleMarkers(data = df.data,
lat = ~lat, lng = ~lon,
label = df.data$entrynames,
color = df.data$colors,
labelOptions = labelOptions(noHide = TRUE,
style = list(
"color" = "gray30",
"font-family" = "serif",
"font-style" = "italic",
"box-shadow" = "3px 3px rgba(0,0,0,0.25)",
"font-size" = "14px",
"border-color" = "rgba(0,0,0,0.5)"
),
textOnly = FALSE,
offset=c(0,0)))
df.entrynames <- c("Entry 1: Some text","Entry 2: More text")
df.lat <- c(51.509898,51.510736)
df.lon <- c(-0.1345093,-0.135190)
df.colors <-c("Blue","Red")
df.sizes <-c(36,2)
df.data <- data.frame(entrynames=df.entrynames,lat=df.lat,lon=df.lon,colors=df.colors,textsizes=df.sizes)
df.data$entrynames <- as.character(df.data$entrynames)
df.data$colors <- as.character(df.data$colors)
df.data$textsizes <- paste(df.data$textsizes,"px",sep="")
#Add a vector to split the data by
df.data$place<-seq(1:nrow(df.data))
library(purrr)
#split the data
ob_place <- df.data %>%
split(., .$place)
#make a map
m <- leaflet() %>%
addTiles()
#Add layers
names(ob_place) %>%
purrr::walk(function(df.data) {
m<<-m %>% #seems like there's supposed to be two carrots here, i had problems without one
addCircleMarkers(data=ob_place[[df.data]],fillColor=~colors,
fillOpacity = 0.6,
weight=1,
radius=13,
color="white",
opacity = .6,
lng=~lon, lat=~lat,
group = "Show All",
label = ~entrynames,
labelOptions = labelOptions(noHide = T,
#direction = ~MyDirection, #https://rstudio.github.io/leaflet/popups.html
textsize = ~textsizes,
#opacity=~opacity,
style = list(
"color"="black",
"font-family" ="sans-serif",
"box-shadow" = "3px 3px rgba(0,0,0,0.25)",
#"font-size" = "12px",
"border-color" = "rgba(0,0,0,0.5)"
)))
})
m
Similar to setting the direction of labels
I'm building a leaflet map on R having multiple layers that are controlled by addLayersControl. Every layer as the same spatial information, so only the data associated to each polylines changes. The idea is to have a basic map, where the user decide which data field is display. I succeeded at making the map, however I noticed that the size of the html file produced is huge.
In my actual context, making the map with only one layer leads to a ~20mb file. However, if I add one field it gets to ~40mb and three layer ~60mb. So it seems to me that the html produced is loading the same shapefile 3 times instead of simply using one shapefile and linking it a data frame of some sort.
Am I stock with this behavior of leaflet or is there a way to file size inflation in my context? I may not have programmed my leaflet the better way...
I've made a reproducible example to show the problem. It uses a small shapefile so the size problem is not dramatic, however the point is the same, which is constantly doubling file size. Also, the example is lengthy, sorry about that, I could'n find a way to simplify it further.
Preparation:
# loading the libraries
library(sf)
library(leaflet)
library(htmlwidgets)
# preparing the shapefile
nc <- st_read(system.file("gpkg/nc.gpkg", package="sf"), quiet = TRUE) %>%
st_transform(st_crs(4326))
# preparing the colors (not really important)
pal.area <- colorNumeric(palette = "inferno", domain = range(nc$AREA))
pal.perim <- colorNumeric(palette = "inferno", domain = range(nc$PERIMETER))
pal.cnty <- colorNumeric(palette = "inferno", domain = range(nc$CNTY_))
pal.sid74 <- colorNumeric(palette = "inferno", domain = range(nc$SID74))
Making the leaflet, this section is long, however it's simply 4 leaflet maps created one after another by adding one layer at a time. It's mostly copy-pasted work:
###
one_layer <- leaflet(data = nc) %>%
addTiles() %>%
addPolylines(fillColor = ~pal.area(AREA),
fill = TRUE,
opacity = 0.8,
group = "area") %>%
addLegend("bottomright",
pal = pal.area, values = ~AREA,
opacity = 1, group = "area"
)
###
###
two_layers <- leaflet(data = nc) %>%
addTiles() %>%
addPolylines(fillColor = ~pal.area(AREA),
fill = TRUE,
opacity = 0.8,
group = "area") %>%
addLegend("bottomright",
pal = pal.area, values = ~AREA,
opacity = 1, group = "area") %>%
addPolylines(fillColor = ~pal.perim(PERIMETER),
fill = TRUE,
opacity = 0.8,
group = "perim") %>%
addLegend("bottomright",
pal = pal.perim, values = ~PERIMETER,
opacity = 1, group = "perim"
) %>%
addLayersControl(
overlayGroups = c("area", "perim"), position = "bottomleft",
options = layersControlOptions(collapsed = FALSE)
)
###
###
three_layers <- leaflet(data = nc) %>%
addTiles() %>%
addPolylines(fillColor = ~pal.area(AREA),
fill = TRUE,
opacity = 0.8,
group = "area") %>%
addLegend("bottomright",
pal = pal.area, values = ~AREA,
opacity = 1, group = "area") %>%
addPolylines(fillColor = ~pal.perim(PERIMETER),
fill = TRUE,
opacity = 0.8,
group = "perim") %>%
addLegend("bottomright",
pal = pal.perim, values = ~PERIMETER,
opacity = 1, group = "perim"
) %>%
addPolylines(fillColor = ~pal.cnty(CNTY_),
fill = TRUE,
opacity = 0.8,
group = "cnty") %>%
addLegend("bottomright",
pal = pal.cnty, values = ~CNTY_,
opacity = 1, group = "cnty"
) %>%
addLayersControl(
overlayGroups = c("area", "perim", "cnty"), position = "bottomleft",
options = layersControlOptions(collapsed = FALSE)
) %>%
hideGroup(c("perim","cnty"))
###
###
four_layers <- leaflet(data = nc) %>%
addTiles() %>%
addPolylines(fillColor = ~pal.area(AREA),
fill = TRUE,
opacity = 0.8,
group = "area") %>%
addLegend("bottomright",
pal = pal.area, values = ~AREA,
opacity = 1, group = "area") %>%
addPolylines(fillColor = ~pal.perim(PERIMETER),
fill = TRUE,
opacity = 0.8,
group = "perim") %>%
addLegend("bottomright",
pal = pal.perim, values = ~PERIMETER,
opacity = 1, group = "perim"
) %>%
addPolylines(fillColor = ~pal.cnty(CNTY_),
fill = TRUE,
opacity = 0.8,
group = "cnty") %>%
addLegend("bottomright",
pal = pal.cnty, values = ~CNTY_,
opacity = 1, group = "cnty"
) %>%
addPolylines(fillColor = ~pal.sid74(SID74),
fill = TRUE,
opacity = 0.8,
group = "sid74") %>%
addLegend("bottomright",
pal = pal.sid74, values = ~SID74,
opacity = 1, group = "sid74"
) %>%
addLayersControl(
overlayGroups = c("area", "perim", "cnty", "sid74"), position = "bottomleft",
options = layersControlOptions(collapsed = FALSE)
) %>%
hideGroup(c("perim","cnty", "sid74"))
###
Then, you get 4 objects (maps) we can compare their size directly in R:
object.size(one_layer)
301864 bytes
object.size(two_layers)
531144 bytes
object.size(three_layers)
681872 bytes
object.size(four_layers)
828616 bytes
The size increase is constant and way higher that what we would expect if the only the data was added instead of all the spatial info. As a comparison, the initial shape which has 15 fields is of size:
object.size(nc)
135360 bytes
If we save the maps to HTML, the problem is even more visible:
saveWidget(one_layer, paste0(getwd(),"/temp_data/temp/one_layer.html"), selfcontained = F)
saveWidget(two_layers, paste0(getwd(),"/temp_data/temp/two_layers.html"), selfcontained = F)
saveWidget(three_layers, paste0(getwd(),"/temp_data/temp/three_layers.html"), selfcontained = F)
saveWidget(four_layers, paste0(getwd(),"/temp_data/temp/four_layers.html"), selfcontained = F)
file.info(list.files("temp_data/temp", pattern = ".html$", full.names = T))$size[c(2,4,3,1)] %>%
setNames(c("One Layer", "Two Layers", "Three Layers", "Four Layers")) %>%
barplot(ylab="size in Bytes")
It's clearly doubling in size.
So, to summarize, is there a way to get leaflet to not reproduced the spatial information when adding multiple fields of data to the same map?
How do you set the layer order in R's leaflet package so that tiles show up on top of polygons filled with color?
Here's what I've got so far:
require(leaflet)
require(acs)
require(tigris)
require(rgdal)
census.income.end.year = 2015
county = 17
nd.counties=acs.fetch(geography=geo.make(state="ND", county=county),
table.number="B01003", endyear = 2015)
tracts <- tigris::tracts(state = 'ND', county = county, cb=FALSE, year = 2015)
# create a geographic set to grab tabular data (acs)
geo<-geo.make(state=c("ND"),
county = county,
tract="*")
# add in median income
median.income <- acs.fetch(endyear = census.income.end.year,
geography = geo,
variable = c("B19013_001"))
income_df <- data.frame(paste0(as.character(median.income#geography$state),
str_pad(as.character(median.income#geography$county), 3, 'left', '0'),
str_pad(as.character(median.income#geography$tract), 5, 'left', '0')),
median.income#estimate)
rownames(income_df)<-1:nrow(income_df)
names(income_df)<-c("GEOID", "hhincome")
income_merged <- geo_join(tracts, income_df, "GEOID", "GEOID")
income_merged <- spTransform(income_merged, CRS("+init=epsg:4326"))
qpal <- colorQuantile("plasma", income_df$hhincome, n = 4)
leaflet() %>%
setView( -96.7898, 46.8772, zoom=11) %>%
addPolygons(data = income_merged,
fillColor = qpal(income_merged$hhincome),
fillOpacity = 1,
weight = 0.3) %>%
addProviderTiles(providers$Hydda.RoadsAndLabels)
Ultimately, I'ld like to do this with addTiles (instead of addProviderTiles as in the above code) using a custom MapBox, but I can't figure out how to make that reproducible for this example... given that you need a key to access custom MapBox tiles (BTW, I've created a custom MapBox tile that should be transparent except for roads and labels, so the underlying polygons should "show thru.")
Here is one way to do add a tile on top of a circle with the non-R version of leaflet: http://jsfiddle.net/dcu9pz2w/, but I don't see how to make that work in my context. I think adding "panes" may be the way to go, but I don't see that functionality in R leaflet. Also, I explored z-index values, but that seemed to be a dead end.
Any help is much appreciated!
R leaflet now includes addMapPane function. The solution to this problem is to first set up pane order and then add tiles/polygons. Reproducible example:
library(leaflet)
library(geojsonio)
# get polygon data
# https://github.com/simonepri/geo-maps/blob/master/info/countries-land.md
world <- geojson_read(
"https://github.com/simonepri/geo-maps/releases/download/v0.6.0/countries-land-10km.geo.json",
what = "sp"
)
# generate random values
world#data$value <- runif(nrow(world#data))
# get color palette
color_pal <- colorNumeric(palette = "YlOrRd", domain = NULL)
# get leaflet map
leaflet() %>%
setView(lat = 50, lng = 15, zoom = 4) %>%
addMapPane("background_map", zIndex = 410) %>% # Level 1: bottom
addMapPane("polygons", zIndex = 420) %>% # Level 2: middle
addMapPane("labels", zIndex = 430) %>% # Level 3: top
addProviderTiles(
providers$Esri.WorldTerrain,
options = pathOptions(pane = "background_map")
) %>%
addPolygons(
data = world, stroke = FALSE, smoothFactor = 0.2,
fillOpacity = 0.6, fillColor = ~color_pal(value),
options = pathOptions(pane = "polygons")
) %>%
addProviderTiles(
providers$Stamen.TonerLabels,
options = pathOptions(pane = "labels")
)